Customer Success Engineer

This is a fully remote position, open to applicants in United Arab Emirates (UAE).

📋 Description

• Assist customers in navigating initial usage milestones by empowering key personas, addressing obstacles, and ensuring the effective use of applications implemented during the onboarding process.

• Oversee application usage, pinpoint underused tools and inactive users, and enhance activation and business outcomes.

• Monitor product usage, user satisfaction, and achievement milestones to identify risks and devise mitigation strategies.

• Advocate for customer technical needs, identify gaps, and communicate enhancement requests to the product and engineering teams.

• Conduct onboarding workshops and training sessions for diverse user groups.

• Provide focused, scalable training sessions and develop reusable knowledge-sharing resources.

• Partner with Engagement Directors to synchronize learning initiatives with business objectives and gather feedback and results for executive reviews.

• Act as the technical liaison among customers, developers, and DataRobot’s AI platform.

• Collaborate with Account Owners, Engagement Directors, and Professional Services teams to expedite time-to-value, facilitate expansion, and minimize churn risk.

⛳️ Requirements

• 3–5+ years of experience in technical customer-facing roles such as Solution Engineer, AI/ML Engineer, Technical CSM, or Application Developer.

• Bachelor's degree in a technical, business, or related field, or equivalent practical experience.

• Knowledge of AI platforms, application lifecycle management, or data-centric solution delivery.

• Experience in GenAI application development, prompt engineering, and familiarity with LLMs.

• Excellent presentation and communication skills for both business users and technical stakeholders.

• Ability to convert complex technical features into quantifiable business results.

• Experience in promoting product adoption, managing customer success strategies, and driving technical engagement.

• In-depth knowledge of the entire machine learning lifecycle, including feature engineering, model training, accuracy assessment, insight generation, and model deployment for inference.

• Understanding of GenAI application architectures and implementations of LLMs.

• Familiar with AWS, Azure, or GCP and their deployment patterns.

• Proficient at reading code and logs to troubleshoot technical challenges.

• Professional fluency in Japanese and English, both written and verbal.

🏝️ Benefits

• Medical, Dental & Vision Insurance.

• Flexible Time Off Program.

• Paid Holidays.

• Paid Parental Leave.

• Global Employee Assistance Program (EAP).